Instructions to use facebook/regnet-x-320 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-320 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-320") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("facebook/regnet-x-320") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-320", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (360c65dade6e3b0fecb3f4cc117fc7c93b7ee238) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>9979163
-
Add TF weights (#1)
joaogante- Add TF weights (2e5613177c8ab13c42129399a1ddf9d9853a1722)bac84c8
-
Upload README.md
7fac3cf
-
Add feature extractor
0b98867 -
Add model
76341d6 -
initial commit
81778f9